The Intersection of Intimate Partner Violence and Traumatic Brain Injury: Findings From an Emergency Summit Addressing System-Level Changes to Better Support Women Survivors
Bibliographic record
Abstract
BACKGROUND: Traumatic brain injury (TBI) occurring during intimate partner violence (IPV) is a largely unrecognized but significant public health crisis. One in 3 women will experience IPV in their lifetime, up to 75% of whom will sustain a TBI as a result. This article reports on the systems-level findings from a national summit to address barriers, needs, and priorities related to healthcare and support services for women survivors of IPV-TBI. OBJECTIVES: (1) To identify key needs, facilitators, and barriers to care for women survivors of IPV presenting with TBI; and (2) to cocreate ideas for resources and principles for identification, clinical care, and support for healthcare practitioners who treat women exposed to IPV and TBI. METHODS: Using a community-based participatory research approach, we engaged 30 stakeholders-drawn from a national IPV-TBI Knowledge-to-Practice (K2P) Network including diverse women survivors, service providers, researchers, and decision makers-in 2 half-day virtual meetings. Data were gathered through small group breakout sessions using semistructured discussion guides. Sessions were recorded, transcribed verbatim, and analyzed using thematic analysis techniques. Stakeholders contributed to the analysis and knowledge translation through member-checking activities. Ethics approval was obtained through the University of Toronto. FINDINGS: Three main systems-level themes arose during these discussions: (1) the need for trauma-informed, anti-racist, and equitable health and social care systems; (2) the need for cross-pollination of knowledge between disciplines; and (3) the need for systems-level support for integrated and coordinated care. This article explores these needs and provides recommendations and suggestions for paths forward. CONCLUSIONS: The findings of this project enhance understanding of system-level needs among women survivors and provide a template for a national agenda for IPV-TBI research and practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".